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  • 1.
    Aalipour, Mojgan
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Singh, Sarbjeet
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Identification of Factors affecting Human performance in Mining Maintenance tasks2014In: Proceedings of the 3rd international workshop and congress on eMaintenance: June 17-18 Luleå, Sweden : eMaintenance, Trends in technologies & methodologies, challenges, possibilites and applications / [ed] Uday Kumar; Ramin Karim; Aditya Parida; Philip Tretten, Luleå: Luleå tekniska universitet, 2014, p. 71-76Conference paper (Refereed)
    Abstract [en]

    This paper investigates the factors affecting humanperformance in maintenance task in mining sector. Theobjective is identify various factors and to classify them asdriving (strong driving power and weak dependence) anddependent factors (weak driving power and strongdependence). The factors were identified through literaturesurvey and are ranked using mean score of data questionnaire.The reliability of measures is pretested by applyingCronbach’s alpha coefficient to responses to a questionnairegiven to maintenance personnel. The interrelationshipsbetween human factors have been recognized by interpretivestructural modeling (ISM). Further, these factors have beenclassified using matrice d'impacts croises-multiplicationappliqué à un classement (MICMAC) analysing. This casestudy will figure out the factors affecting human performancefor deriving maintenance management insights to improveproductivity in the mining sector. Further, this understandingmay be helpful in framing the policies and strategies formining industry. Temperature, lighting, documentation,communication and fitness are driving factors. Moreover,Work layout, tools availability, complex tasks, time pressure,safety, boss decisions, training, fatigue and motivation havestrong driving power as well as high dependencies and itcomes under the category of linkage factors.

  • 2.
    Björling, Sten-Erik
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Baglee, David
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Singh, Sarbjeet
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Maintenance knowledge management with fusion of CMMS and CM2013In: DMIN 2013 International Conference on Data Mining: 22nd -25th July 2013, Las Vegas, Nevada, USA, 2013Conference paper (Refereed)
    Abstract [en]

    Maintenance can be considered as an information, knowledge processing and management system. The management of knowledge resources in maintenance is a relatively new issue compared to Computerized Maintenance Management Systems (CMMS) and Condition Monitoring (CM) approaches and systems. Information Communication technologies (ICT) systems including CMMS, CM and enterprise administrative systems amongst others are effective in supplying data and in some cases information. In order to be effective the availability of high-quality knowledge, skills and expertise are needed for effective analysis and decision-making based on the supplied information and data. Information and data are not by themselves enough, knowledge, experience and skills are the key factors when maximizing the usability of the collected data and information. Thus, effective knowledge management (KM) is growing in importance, especially in advanced processes and management of advanced and expensive assets. Therefore efforts to successfully integrate maintenance knowledge management processes with accurate information from CMMSs and CM systems will be vital due to the increasing complexities of the overall systems.Low maintenance effectiveness costs money and resources since normal and stable production cannot be upheld and maintained over time, lowered maintenance effectiveness can have a substantial impact on the organizations ability to obtain stable flows of income and control costs in the overall process. Ineffective maintenance is often dependent on faulty decisions, mistakes due to lack of experience and lack of functional systems for effective information exchange [10]. Thus, access to knowledge, experience and skills resources in combination with functional collaboration structures can be regarded as vital components for a high maintenance effectiveness solution.Maintenance effectiveness depends in part on the quality, timeliness, accuracy and completeness of information related to machine degradation state, based on which decisions are made. Maintenance effectiveness, to a large extent, also depends on the quality of the knowledge of the managers and maintenance operators and the effectiveness of the internal & external collaborative environments. With emergence of intelligent sensors to measure and monitor the health state of the component and gradual implementation of ICT) in organizations, the conceptualization and implementation of E-Maintenance is turning into a reality. Unfortunately, even though knowledge management aspects are important in maintenance, the integration of KM aspects has still to find its place in E-Maintenance and in the overall information flows of larger-scale maintenance solutions. Nowadays, two main systems are implemented in most maintenance departments: Firstly, Computer Maintenance Management Systems (CMMS), the core of traditional maintenance record-keeping practices that often facilitate the usage of textual descriptions of faults and actions performed on an asset. Secondly, condition monitoring systems (CMS). Recently developed (CMS) are capable of directly monitoring asset components parameters; however, attempts to link observed CMMS events to CM sensor measurements have been limited in their approach and scalability. In this article we present one approach for addressing this challenge. We argue that understanding the requirements and constraints in conjunction - from maintenance, knowledge management and ICT perspectives - is necessary. We identify the issues that need be addressed for achieving successful integration of such disparate data types and processes (also integrating knowledge management into the “data types” and processes).

  • 3.
    Illankoon, Prasanna
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Manathunge, Yamuna
    Department of Education and Training, University of Vocational Technology, Ratmalana, Sri Lanka.
    Tretten, Phillip
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Abeysekara, John
    Work Science Academy, Kandana, Sri Lanka.
    Singh, Sarbjeet
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Lockout and Tagout in a Manufacturing Setting from a Situation Awareness Perspective2019In: Safety, ISSN 2313-576X, Vol. 5, no 2Article in journal (Refereed)
    Abstract [en]

    Applying lockouts during maintenance is intended to avoid accidental energy release, whereas tagging them out keeps employees aware of what is going on with the machine. In spite of regulations, serious accidents continue to occur due to lapses during lockout and tagout (LOTO) applications. Few studies have examined LOTO effectiveness from a user perspective. This article studies LOTO processes at a manufacturing organization from a situation awareness (SA) perspective. Technicians and machine operators were interviewed, a focus group discussion was conducted, and operators were observed. Qualitative content analysis revealed perceptual, comprehension and projection challenges associated with different phases of LOTO applications. The findings can help lockout/tagout device manufacturers and organizations that apply LOTO to achieve maximum protection.

  • 4.
    Kyriakidis, Miltos
    et al.
    ETH Zurich, Future Resilient Systems, Singapore - ETH Centre, Singapore.
    Simanjuntak, Samuel
    Centre for Transport Studies, Imperial College London, United Kingdom.
    Singh, Sarbjeet
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Majumdar, Arnab
    Centre for Transport Studies, Imperial College London, United Kingdom.
    The indirect costs assessment of railway incidents and their relationship to human error: The case of Signals Passed at Danger2019In: Journal of Rail Transport Planning & Management, ISSN 2210-9706, E-ISSN 2210-9714, Vol. 9, p. 34-45Article in journal (Refereed)
    Abstract [en]

    The majority of railway incidents result neither in passenger nor operators harm, nor they lead to any severe damage on the rolling stock or the infrastructure. Nevertheless, such incidents result in financial loses, broadly known as indirect costs, which are difficult to identify, isolate, evaluate, and quantify. This paper introduces a framework to quantify the indirect costs in railway operations. Furthermore, as degraded human performance remains a major contributor to operational errors and railway incidents, this study explores for associations between the indirect costs and the factors that affect and contribute to degraded human performance. The framework was implemented in the calculation of the Category A1 Signals Passed at Danger (SPADs) indirect costs. Data was obtained from two UK train operators, while the associated human performance was analysed using the Railway-Performance Shaping Factors (R-PSFs) taxonomy. Employing Spearman's rank order correlation and Fisher's exact statistical tests the associations between R-PSFs and indirect costs were reviewed. Results show significant correlations between the R-PSFs and indirect costs, but only if the importance and severity of every individual R-PSFs is considered. We expect our findings to aid the relevant stakeholders on their efforts to make better decisions on improving safety performance of railway operations.

  • 5.
    Nadakatti, Mahantesh
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Singh, Sarbjeet
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Parida, Aditya
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Machine health monitoring: an integrated maintenance approach2012In: Proceedings of the 2nd International Workshop & Congress on eMaintenance: Dec 12-14 Luleå, Sweden : eMaintenace: trends in technologies and methodologies, challenges, possibilities and applications / [ed] Ramin Karim; Aditya Parida; Uday Kumar, Luleå: Luleå tekniska universitet, 2012, p. 107-112Conference paper (Refereed)
  • 6.
    Oliveira, Ruben
    et al.
    CEMUC® – University of Coimbra's Mechanical Engineering Research Center, University of Coimbra.
    Farinha, Torres
    CEMUC® – University of Coimbra's Mechanical Engineering Research Center, University of Coimbra.
    Singh, Sarbjeet
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    An augmented reality application to support maintenance – is it possible?2013In: MPMM 2013 (Maintenance Performance Measurement and Management), Lappeenranta, Finland, 2013, p. 260-271Conference paper (Refereed)
    Abstract [en]

    Augmented Reality (AR) is a trend technology with many applications for domestic consumers. On the past it was developed significant projects with the objective to introduceAR in industrial environments, but did those projects be succeeded?AR looks like to be a powerful technology, but can it be applied to industrial environments? And for the Maintenance sector in particular?This paper pretends to answer the above questions and explain how to overcome restrictions detected on previous projects by presenting some results from a project under development, (Oliveira et al., 2012).It will also be presented a Computer Maintenance Management Systems (CMMS) called SMIT (Farinha et al., 2008) and its innovations with the integration of modules like active 3D models for technical assets and an AR module.Machines are enabled to do more and more complex tasks and, consequently, their aintenance is becoming more complex too. This gain of complexity might need new tools to support maintenance interventions and also demands new methodologies to implement for the technicians training in order to perform a better apprenticeship aiming to minimize the cost of each maintenance intervention. AR can give a great contribute to enhance training conditionsand technicians capabilities.

  • 7.
    Singh, Sarbjeet
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Baglee, David
    Institute for Automotive Manufacturing and Advanced Practices, University of Sunderland.
    Knowles, Michael
    Institute for Automotive Manufacturing and Advanced Practices, University of Sunderland.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Developing RCM strategy for wind turbines utilizing e-condition monitoring2015In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 6, no 2, p. 150-156Article in journal (Refereed)
    Abstract [en]

    Renewable energy sources such as wind energy are available without any limitations. In order to extract this energy efficiency, the reliability of such technologies is critical if pay back periods and power generation requirements are to be met. Due to recent developments in the field of wind engineering and in particular the expansion of installed capacity around the world, the need for reliable and intelligent diagnostic tools is of greater importance. The number of offshore wind turbines installed in the seas around Britain’s coasts is likely to increase from just fewer than 150–7,500 over the next 10 years with the potential cost of £10 billion. Operation and Maintenance activities are estimated to be 35 % against the cost of electricity. However, the development of appropriate and efficient maintenance strategies is currently lacking in the wind industry. The current reliability and failure modes of offshore wind turbines are known and have been used to develop preventive and corrective maintenance strategies which have done little to improve reliability. In addition, the failure of one minor component can cause escalated damage to a major component, which can increase repair and or replacement costs. A reliability centered maintenance (RCM) approach offers considerable benefit to the management of wind turbine operations since it includes an appreciation of the impact of faults on operations. Due to the high costs involved in performing maintenance and the even higher costs associated with failures and subsequent downtime and repair, it is critical that the impacts are considered when maintenance is planned. This paper provides an overview of the application of RCM and on line e-condition monitoring to wind turbine maintenance management. Unplanned maintenance levels can be reduced by increasing the reliability of the gear box and individual gears through the analysis of lubricants. Finally the paper will discuss the development of a complete sensor-based processing unit that can continuously monitor the wind turbines lubricated systems and provide, via wireless technology, real time data enabling on shore staff with the ability to predict degradation anticipate problems and take remedial action before damage and failure occurs

  • 8.
    Singh, Sarbjeet
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Bending moment assessment at L5/S1 and parameter optimization using Taguchi design during lifting task2012In: Journal of Ergonomic Study, ISSN 2076-5517, Vol. 14, no 2, p. 79-89Article in journal (Refereed)
    Abstract [en]

    This paper reports on the investigation of the effect of lifting parameters on bending moment at the lower back. The experimental study has been conducted under varying load weights, horizontal location of load from L5/S1 and lifting technique (stoop, full squat and lifting device). The design of experiments approach using Taguchi’s orthogonal array was used. The level of importance of the parameters on bending moment has been determined using the analysis of variance (ANOVA). After implementing a lifting device 26-34 % reduction in bending moment at L5/S1 has been observed.

  • 9.
    Singh, Sarbjeet
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Galar, Diego
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Baglee, David
    Department of Computing, Engineering and Technology, Institute for Automotive and Manufacturing Advanced Practise, University of Sunderland.
    Björling, Sten-Erik
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Self-maintenance techniques: a smart approach towards self-maintenance system2014In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 5, no 1, p. 75-83Article in journal (Refereed)
    Abstract [en]

    The modern systems operating at varying conditions brought a new paradigm shift to in-machine renovation and repair. These systems often encounter an infinite collection of clumsy diagnostic tools and applications that decrease agility, increase time-to-repair, and increase management overheads. One approach is to remove the human and potential costly and time consuming human errors, from the diagnosis of faults and implementation of a maintenance strategy. In order to achieve this it is necessary to develop systems that support advanced intelligent maintenance systems or smart maintenance technologies. Self-maintenance machines can be a better option with the capabilities of condition monitoring, diagnosing, repair planning and executing in order to extend the life and performance of equipment. The objective of this paper is to discuss the concept of self-maintenance, need of self-maintenance, potential scenarios where self-maintenance can be successfully implemented and issues related to self-maintenance machines. It has been concluded that the aim is to have self-maintenance system in order to make a machine capable of reconfiguration, compensation, and self-maintenance.

  • 10.
    Singh, Sarbjeet
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Rupesh
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Applying human factor analysis tools to a railway brake and wheel maintenance facility2015In: Journal of Quality in Maintenance Engineering, ISSN 1355-2511, E-ISSN 1758-7832, Vol. 21, no 1, p. 89-99Article in journal (Refereed)
    Abstract [en]

    PurposeThis paper demonstrates three techniques to extract human factor information from specific railway maintenance tasks. It describes the techniques and shows how these tools can be applied to identify improvements in maintenance practices and workflow. Design/methodology/approachThree case studies were conducted on single group of technicians (N=19) at a railway maintenance workshop in Luleå, Sweden. Case study I examined the posture of the technicians while they were changing the brake shoes of freight wagons; the study employed the Standard Nordic Questionnaire and a videotape using the Ovako Working Posture Analysis System (OWAS). Case study II looked at maintenance repair times required to change the wheel axle on freight wagons at the workshop. A video filming method suggested by the European Agency for Safety and Health at Work was used to measure actual maintenance time. Finally, case study III considered the technicians’ (N=19) perception of work demands, their control over the work and their social support while performing maintenance tasks (brake shoe and wheel axle maintenance); to this end, the case study used a demand control support questionnaire. FindingsIn the first case study, the Standard Nordic Questionnaire confirmed that technicians at this particular railway vehicle maintenance workshop suffer from back and shoulder pain. The Ovako Working Posture Analysis showed that 21% of the working time required to fit the brake wedge and cotter pin fits into two OWAS categories: category 3, where “change is required as soon as possible,” and category 4, where “change is required immediately”. Problems stem from poor workplace layout, incorrect posture and inaccessibility of tools and components. In the second study, the video analysis indicated that the working time to change the wheel axle of a freight wagon is greatly affected by poor workplace layout. The third case study showed that the technicians have lower “psychological demands” (mean=13), “higher control over work” (mean= 16) and “high social support” (mean= 22).Practical implicationsThe objective of this study was to apply knowledge about human factors to the functional relationships between maintenance personnel, tasks and the working environment to improve safety. If the workplace layout, working posture, maintenance manuals and accessibility of tools are poorly planned, maintenance performance can be adversely affected. The results of this study should assist maintenance management to design new policies and guidelines for improving the work environment.Originality/valueThree case studies were conducted at a railway maintenance workshop in Luleå, Sweden, to collect data on how human factors affect various railway maintenance tasks.

  • 11.
    Singh, Sarbjeet
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Rupesh
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Modelling factors affecting human operator failure probability in railway maintenance tasks: an ISM-based analysis2015In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 6, no 2, p. 129-138Article in journal (Refereed)
    Abstract [en]

    This paper investigates the factors affecting human operators’ probability of failure when performing railway maintenance tasks. The objective is to understand the interaction of the various factors and to identify driving and dependent factors. The factors are identified through a survey of the literature and ranked using a Likert scale. The reliability of measures is pretested by applying Cronbach’s alpha coefficient to responses to the questionnaire given to maintenance personnel. An interpretive structural model is presented, and factors are classified using matrice d’impacts croises-multiplication appliquéà un classement (MICMAC). The research may help maintenance management understand the interaction of factors affecting human failure probability in railway maintenance and help management devise policies and guidelines for railway maintenance related tasks.

  • 12.
    Singh, Sarbjeet
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Majumdar, Arnab
    The Lloyd's Register Foundation Transport Risk Management Centre Centre for Transport Studies, Imperial College London London, UK.
    Kyriakidis, Miltos
    ETH Zurich, Future Resilient Systems, Singapore ETH Centre, Singapore .
    Incorporating Human Reliability Analysis to enhance Maintenance Audits: The Case of Rail Bogie Maintenance2017In: International Journal of Prognostics and Health Management, ISSN 2153-2648, E-ISSN 2153-2648, Vol. 8, article id 062Article in journal (Refereed)
    Abstract [en]

    Human errors occurring during railway maintenance activities can significantly reduce the availability of equipment. Identification of potential human errors, their causes and prediction of the associated probabilities are important stages in order to manage such errors. This paper investigates the probability of human error during the maintenance of railway bogies. A case study examines technicians performing maintenance on the disc brake assembly unit, wheel set, and bogie frame under various error producing conditions in a railway maintenance workshop in Luleå, Sweden. The Human Error Assessment and Reduction Technique (HEART) is employed to determine the probability of human error occurring during each of the maintenance tasks, while fault tree analysis is used to define the potential errors throughout the maintenance process. The probability of a technician committing an error during the maintenance of the disc brake assembly, wheel set, and bogie frame is found to be 0.20, 0.039 and 0.021 respectively, with the human error probability (HEP) for the entire bogie 0.24. Time pressure, ability to detect and perceive problems, over-riding information, the need to make decisions and mismatches between the operator and designer’s model turn out to be major contributors to human error. These findings can help maintenance management personnel to better understand the error producing conditions that may lead to errors and in turn serve as an input to modify policies and guidelines for railway maintenance tasks.

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